Device and method for identifying and quantifying layered substances

ABSTRACT

An apparatus for identifying and measuring in real time substances overlying a surface comprises a plurality of electrodes, a temperature sensor, an electrode control system connected to the plurality of electrodes for defining an electric field, an amplitude and phase measurement system connected to the plurality of electrodes and to the electrode control system for measuring a plurality of currents responsive to the electric field and converting the currents to a measurement set and computer for storing a map comprising a partition of a vector space of predetermined characteristics of substances into regions of profiles corresponding to the substances which could be overlying the surface. The computer correlates the measurement set with the map thereby identifying and quantifying the substances overlying the surface and generates an output signal corresponding to the identity and quantity of substances overlying the surface. A display responsive to the output signal displays the identity and quantity of substances overlying the surface.

FIELD OF INVENTION

This invention relates to a device and method for the non-intrusive andspatial interrogation of substances to identify and quantify thesubstances from measurements dictated by the dielectric profile of thesubstances. In particular, this invention relates to a device and methodof detecting an accumulation of air, water, ice, snow or variety ofpossible contaminants such as de-icing fluid on aircraft surfaces.

BACKGROUND OF INVENTION

Ice accumulation on aircraft surfaces has been a problem since theinception of the aviation industry. The accumulation of ice has fourmain effects which are all negative and in some instances catastrophic.First, aerodynamic performance is severely restricted resulting in aloss of lift and increase drag. Second, the accumulation of iceincreases the aircraft weight. Third, the accumulation of ice willimpair or restrict the movement of control surfaces. Fourth, the ice maybe ingested into the engine or other system intakes terminating engineoperation.

Recently, interest in aircraft icing has been greatly heightened with anincrease in industry and public awareness of the hazards associated withthis problem. Although the detrimental effects of ice build up onaircraft performance has been generally well acknowledged, difficultiesin predicting or measuring ice accumulation on aircraft has preventedrigorous and reliable procedures for flight crews both on the ground andin the air to minimize this problem.

The problem of aircraft icing occurs in two broad categories. First,inflight icing occurs on the leading edge of the airfoil. This type ofice build up is common and is handled by pilot observations or pilotawareness or suspicions of impending icing conditions. In many aircraft,the leading edges of the wing are heated by engine bleed air attemperatures of up to 250° C. Engine air bleed is normally done atregular intervals when icing conditions are likely regardless as towhether any ice has accumulated. A percentage of engine air is requiredto be used to heat the aircraft wing rather than for propulsionpurposes. It is very inefficient to bleed engine air when no ice hasaccumulated on the aircraft surface.

The second category of aircraft icing is ground icing. Ground icingoccurs over the top of the aircraft surface when the aircraft isstanding. Icing on the leading 10% of the wing has the most criticalaerodynamic effect. This type of ice accumulation is handled by theapplication of de-icing or anti-icing fluids. The problem is amplifiedsince de-icing depends not only on how well the de-icing was undertakenbut also whether ice has re-accumulated since de-icing.

On current commercial aircraft, pilots have no reliable way of judgingthe amount of ice accumulated on the surface of the aircraft bothinflight and on the ground. Further, pilots have no means of assessingthe status of the de-icing or anti-icing fluids which may have beenapplied in accordance with current flight procedures. Pilots areaccordingly faced with difficult decisions on a regular basis in orderto maintain flight schedules.

Several devices have been proposed which are designed to detect thepresence of ice which has accumulated on the aircraft surface. One suchdevice will vibrate an aircraft surface at a known frequency. When theaircraft surface vibrates at a different frequency, the presence of icehas been detected.

Still other devices have been proposed which detect the presence andthickness of ice on an aircraft surface. Such devices have beendescribed in detail in U.S. Pat. No. 4,766,369, Weinstein. This deviceuses two capacitive gauges and a temperature gauge. The ratio of thevoltages of sense side of the capacitive gauges determines the thicknessof the ice present.

Although, these devices may detect the presence of ice on an aircraftsurface it cannot detect the presence of substances other than ice suchas snow, slush, de-icing fluid or dirt. In fact, there are no knowndevices which can detect the presence of snow on an aircraft surface.

Devices and analytical techniques exist for non-intrusive interrogationof materials to deduce their physical properties. Dielectric sensors andanalytical techniques measure the spatial profile of permittivity of amaterial by multiple wavelength interrogation. A spatially periodicfield is imposed upon the material via a first electrode under thecontrol of a wavelength controller. A second or sense electrode is thenused to measure the effect of the material on the charge induced by thefirst electrode in response to the periodic field. By varying thewavelength, spatial distribution of complex permittivity is deduced as afunction of the temporal frequency. The physical properties of thematerial can then be deduced.

Such devices are used to monitor material changes such as the outgassingof solvents from paints, the removal of moisture from coatings, thediffusion of dopants into semi-conductors and the deposition ofmaterials. Such devices and techniques are more fully described in U.S.Pat. No. 4,814,690, Melcher, et al. and U.S. Pat. No. 5,015,951,Melcher.

Initially, it was believed that such devices and techniques would beuseful in the detection of ice accumulation on an aircraft surface.However when attempts were made using such sensors to detectaccumulation of ice on aircraft surfaces, the analytical techniques ofMelcher, et al. were found to be highly unstable and could not in realtime accurately and reliably detect, identify and measure the thicknessof the various contaminants accumulating on the aircraft surface.

One of the problems of the approach of Melcher et al. is that theelectric potential along a planar electrode array must be sufficientlydefined and known at all times. The electric potential is required sothat the theoretical models can be used to predict the spatialpermittivity profile of the measured substance. However, the electricpotential varies depending on the electrical properties of the substancebeing measured. Since the various substances which can accumulate on theaircraft surface are not known beforehand, Melcher et al., wasunsuitable for use as a substance detector.

Melcher also requires sampling to be of a laboratory-quality so that thenon-analyticity problems such as irregularity of the surface and complexstructures could be avoided. Even with approximations, real time dataprocessing was not possible. Data analysis using Melcher's techniques isnormally in the order of hours.

Dielectric sensors measure the effects that the interrogated substancehas on the capacitance of the imposed field. The problems of air gaps ondielectric sensors are well known (see U.S. Pat. No. 5,045,798, Hendrickand U.S. Pat. No. 5,095,278, Hendrick). Air gaps severely limit thesensors' ability to measure the dielectric properties since air and avacuum have the lowest theoretically possible permittivity. Further, airalso induces noise into the capacitance measurement.

SUMMARY OF INVENTION

It is therefore desirable to provide a device and method for conductingnon-intrusive interrogations of substances to identify and quantifyacross a spatial profile, a wide range of substances in real time.

It is further desirable to provide an electrode configuration to definepotential fields to provide spatial measurements by spatially varying aninterrogation signal and analyzing the attenuated response therebyidentifying and quantifying in real time the layered substances causingsuch attenuation.

In one aspect of the invention, there is provided an electrode structurewhich is formed by a plurality of concentric electrodes and a potentialfield shaper which can be implemented by electronic switches to apply aplurality of discreet voltage patterns to each electrode to define apotential field and current measurements are taken from one of theelectrodes. The measurements are analyzed in real-time to identify andquantify the substances overlying the electrode.

In a further aspect of the invention, there is provided an electrodestructure which is formed by a plurality of concentric electrodes and apotential field shaper which applies a discreet voltage to the electrodeto define a potential field and the current measurements are taken frompredetermined electrodes. The measurements are analyzed in real time toidentify and quantify the substances overlying the electrode.

In a further aspect of the invention, the electrode structure can beformed by a plurality of concentric electrodes and the implied field isfixed and the measurement of the signal can be taken from differentelectrodes.

In a further aspect of the invention, an apparatus for identifying andmeasuring in real time substances overlying a surface comprises:

a sensor head comprising a protective layer having a top surface, anelectrode layer having a plurality of electrodes imbedded therein, abacking layer having temperature sensors for generating a signaldependent on temperature and a ground plane layer, connector pinsextending from the plurality of electrodes and the temperature sensorthrough the backing layer and insulated from the ground plane layer, agrounding pin for grounding one electrode to the ground plane layer, thelayers integrally moulded together,

an electrode control system connected to the plurality of electrodes fordefining an electric field at the top surface, the electric fieldapproximating a Bessel function,

an amplitude and phase measurement system connected to the plurality ofelectrodes and to the electrode control system for measuring thecurrents responsive to the electric field and converting the currentresponse to a measurement set comprising at least seven dimensionalregions defined by three complex measurements of impedance andtemperature, and

computer means for storing a map means comprising a partition of avector space of predetermined characteristics of substances into regionsof profiles corresponding to the substances which could be overlying thesurface, said computer means for correlating the measurement set withthe map means thereby identifying and quantifying the substancesoverlying the surface and for generating an output signal correspondingto the identity and quantity of substances overlying the surface, and

display means responsive to the output signal for displaying theidentity and quantity of substances overlying the surface.

In still yet another aspect of the invention, a second computer meansstores a database comprising sample data of sample measurements of theprobable substances and quantities thereof together with estimates ofcorresponding profiles of the sample data and theoretical data of theprobable substances and quantities thereof together with correspondingprofiles of the theoretical data, the second computer means remote fromsaid first computer means, the map means is generated by a secondcomputer means by

(a) selecting the probable substances which are likely to be overlyingthe surface,

(b) selecting data from the database corresponding to the probablesubstances,

(c) successively dividing the selected data into subsets until eachsubset satisfies a predetermined criteria for subdividing;

(d) defining a set of boundary functions, each of which describe ahierarchial boundary between the subsets;

(e) defining a set of profile functions, each of which describe thedistribution of the data in each subset; and

(f) collecting the sets of boundary and profile functions in a mapmeans.

In still yet another aspect of the invention, the computer correlatesthe measurement set with the generated map means by

(a) defining a local profile by applying the measurement set to the mapmeans,

(b) refining the local distribution by numerical dithering of themeasurement set,

(c) calculating the variation of the refined local distribution,

(d) comparing the variation with a predetermined limit and if thevariation is greater than a predetermined limit, sending the outputsignal that the substance has not been identified and if the variationis less than or equal to the predetermined limit sending the outputsignal corresponding to the identity and quantity of the substancesdetected.

In still yet another aspect of the invention, there is provided a methodfor identifying and measuring substances overlying a surface using aplurality of concentric electrodes underlying a surface, an electrodecontrol means connected to the plurality of electrodes for defining anelectric field at the surface, an amplitude and phase measurement meansconnected to the plurality of electrodes and electrode control means formeasuring the currents responsive to the electric field, computer meansfor storing a map means comprising a partition of a vector space ofpredetermined characteristics of substances into regions of profiles,and a display means responsive to an output signal for displaying theidentity and quantity of substances overlying the surface. The methodcomprising the steps of:

(a) applying an electric field at the surface,

(b) measuring currents responsive to the electric field,

(c) converting the currents to a measurement set, and

(d) defining a local profile by applying the measurement set to the mapmeans,

(e) refining the local distribution by numerical dithering of themeasurement set,

(f) calculating the variation of the refined local distribution,

(g) comparing the variation with a predetermined limit and if thevariation is greater than a predetermined limit, sending the outputsignal that the substance has not been identified and if the variationis less than or equal to the predetermined limit sending the outputsignal corresponding to the identity and quantity of the substancesdetected;

(h) generating an output signal corresponding to the identity andquantity of substances overlying the surface; and

(i) after a fixed period of time, repeating the process.

According to yet another aspect of the invention, a method of generatinga map is provided by

(a) selecting the probable substances which are likely to be overlyingthe surface,

(b) selecting data from a database corresponding to the probablesubstances, said database comprises sample data of sample measurementsof the probable substances and quantities thereof together withestimates of corresponding profiles of the sample data and theoreticaldata of the probable substances and quantities thereof together withcorresponding profiles of the theoretical data,

(c) successively dividing the selected data into subsets defining a setof boundary functions describing hierarchial boundaries between thesubsets, the subsets being divided until each subset satisfies apredetermined criteria for subdividing,

(d) defining a set of profile functions describing the distribution ofthe data in each subset;

(e) collecting the set of boundary and profile functions in a map.

DETAILED DESCRIPTION OF THE DRAWINGS

In drawing which illustrate embodiments of the invention,

FIG. 1 is a block diagram of the preferred embodiment of the invention,

FIG. 2 is a top plan view of the sensor head of embodiment of FIG. 1;

FIG. 3 is a side elevational view of the sensor head of FIG. 2;

FIG. 4 is an exploded view of the sensor head of FIG. 2;

FIG. 5 is partial side sectional view of the sensor head of FIG. 2 longthe lines 5--5;

FIG. 6 is a block diagram of the embodiment of FIG. 1, illustrating anelectrode structure of concentric rings;

FIG. 7 is a block diagram of the software routine of the embodiment ofFIG. 1;

FIGS. 8A, 8B, 8C are the applied voltage patterns of the embodiment ofFIG. 1;

FIGS. 9A, 9B, 9C are illustrations of alternate electrode configurationswhich may used in the embodiment of FIG. 1; and

FIG. 10 is a block diagram of a second embodiment of FIG. 1,illustrating an electrode structure of concentric rings.

DETAILED DESCRIPTION OF THE INVENTION

The underlying physics governing the functional performance of thedevice of the present invention are based on the electroquasistaticsubset of Maxwell's equations:

    ∇·εE'=ρ'

    ∇×E'=0 ##EQU1## where the variables are defined as follows: E' electric field intensity

ρ' free charge density

ε absolute permittivity

σ conductivity

For purposes of illustration, the material under study is approximatedby horizontal layers (parallel to the sensor) in which the electricalproperties are constant, and that all primed quantities vary as e^(j)ωt(where j is the square root of -1, ω is the angular frequency ofexcitation, and t is the time) allows the reduction of the above systemto the determination of a Laplacian potential, Φ, within any given layerto the scalar equation:

    ∇.sup.2 Φ=0

where

    -∇Φ=E

At a boundary between layers the following jump conditions hold:##EQU2## where ε=ε-σ/jω and n is the unit vector normal to thepotential.

For a cylindrically concentric electrode embodiment the problem iscylindrically symmetric normal to the sensor surface. The potentialfunction is decomposed into the natural eigenfunctions: ##EQU3## whereJ_(o) (λ_(m) r_(o))=0, J_(i) is the ith Bessel function, z is thecoordinate normal to the sensor surface, r is the radial distance fromthe original, and r_(o) is chosen large enough so that the potential isessentially zero beyond it.

These equations are then solved to yield an expression for the idealcharge density, and hence the current, on the surface of the electrode.This is only an approximate solution as the electric potential betweenthe electrodes has not been specified.

For a structure consisting of k finite layers bounded away from thesensor by an infinite uniform material (i.e. the atmosphere), thecurrent on an electrode of inner and outer radii r₁ and r₂ respectivelyis given by: ##EQU4## where for n<k+1 we have: ##EQU5## while L_(m),k+1=-1 and Δ_(n) is the thickness of the nth layer.

The actual measurements are made in the form of impedances, orequivalently, as admittances (the reciprocal of impedance). The modelmust also account for the contribution to the total admittance of eachpattern made by the fields generated by the support electronics. Becausethis contribution is independent of the material above the sensor, thetotal admittance can be written as:

    A.sub.total =I/P+A.sub.strays

where P is the potential on the sensing electrode and A_(strays) is thecontribution from the support electronics.

The device of the present invention is schematically illustrated inFIG. 1. The invention generally comprises a sensor head 12, electrodecontrol 14, amplitude and phase measurement system 16, communicationssystems 18 and computer and output display system 20. Preferably,computer 20 is at least a computer having an INTEL 286 or equivalentprocessor using standard RS232 connections and the display is aconventional monitor.

Referring to FIGS. 2 and 3, sensor head 12 of the preferred embodimenthas a circular outline in plan view and a slim profile. Extending belowthe sensor head is a plurality of connector pins 22.

The construction of sensor head 12 is illustrated in detail in FIGS. 4and 5. The sensor head has a protective layer 24 on the top surface.Immediately below the protective layer 24 is electrode layer 25 havingimbedded therein electrodes 26. Below the electrode layer 25 is backinglayer 28. On the bottom surface is a ground plane layer 30. Atemperature sensor or thermistor 29 is embedded in backing layer 28.Thermistor 29 is electrically connected to a pair of connector pins forexternal connection. Thermistor 29 allows temperature measurements to betaken.

Protective layer 24 and backing layer 28 are preferably made ofberyllium oxide. Beryllium oxide has a high thermal conductivity whichis similar to aluminum and is electrically insensitive to temperature.Other materials could be used provided such material has good thermalconductivity, is electrically insulating and is electrically insensitivefrom at least -55° to 86° C. but preferably between -65° to 100° C.

The electrodes 26 are embedded in electrode layer 25 in an epoxy or aglass substance 32. A plurality of bores 34 extend axially throughbacking layer 28. In the preferred embodiment, the configuration ofelectrodes 26 is a plurality of concentric circular electrodes.

As noted in detail later, this configuration can be represented incylindrical coordinates and the resulting voltage pattern can then betransformed mathematically by a Bessel series. The cylindricalconfiguration allows the voltage pattern to be represented in onedimension because the voltage level along the electrode plane isindependent of angular position and only dependent on the radialposition from the centre.

The number and width of the electrodes and the radial separation aregoverned by the maximum allowable size of the sensor, the maximumaccretion thickness that must be detected, and the required sensitivityand accuracy of the measurements.

The penetration depth of the electric field from the sensor depends onthe distribution of spatial wavelength information at the electrodes.Different electrode configurations can be obtained to concentratemeasurement sensitivity at desired depths in the substance being sensed.The sensitivity of a given configuration can be optimized by selecting aconfiguration that will maximize the energy from the desired spatialcomponent. A great number of electrodes will facilitate increasedflexibility in the selection of optimum configurations.

Connector pins 22 extend through the bores 34 and are in electricalcontact with the electrode tings 26. Ground plane layer 30 has aplurality of openings 31 allowing connector pins 22 to be insulated fromcontact therewith.

In the preferred embodiment, the outermost ring of electrodes 26 isgrounded. The inside surface of the outermost of bores 34 has ametallized surface 36. The outermost of connector pins 22 is brazed tothe metallized surface 36 to form a hermetic joint 38.

As illustrated schematically in FIG. 1, sensor head 12 is electricallyconnected through connector pins 22 to electrode control 14 andamplitude and phase measurement system 16.

Electrode control 14 is schematically illustrated in FIG. 6. Electrodecontrol 14 comprises a signal source 50 connected to a multiple voltagegenerator 52. The multiple voltage generator feeds a signal selector 54.A digital pattern control 56 also feeds the signal selector 54 todetermine the voltage that is applied to each electrode. Each of theoutputs of the signal selector 54 are connected in parallel to each ringof the electrodes 26, with the exception of ring e. Ring e is feddirectly from sense circuit 58. Signal selector 54 also feeds sensecircuit 58 which in turn feeds ring e.

The amplitude and phase measurement system 16 comprises a sense circuit58, a vector voltage measurement circuit 60 and digitization 61. Sensecircuit: 58 is responsive to signal selector 54 and applies both theinput voltage to ring e and monitors the resulting current in ring e.Sense circuit 58 will output two signals which are representations ofthe applied voltage and the resulting current. The two signals are fedto the vector voltage measurement circuit 60 that produces voltagelevels which correspond to the magnitudes and relative phase of the twosignals. Digitization 61 digitizes the two signals into a digital formatand delivers the digitized signals to communications system 18.

The communications system 18 comprises a digital measurement controlcircuit 62 which is a microprocessor based control. The digitalmeasurement control 62 controls the pattern generation and measurementsequences. It also controls the calibration and monitoring routines andformats the data for outputting to the computer 20.

The circuits illustrated in FIGS. 6 and 10 are known standard electroniccircuits. The circuits are electrically connected in a conventionalmanner to achieve the desired results.

The electrode control 14 can operate in one of two ways. Both waysprovide equally satisfactory results. Referring to FIG. 6, the electrodecontrol 14 could successively apply several discrete voltage patterns tothe electrodes 26 to define a series of potential fields. Only onedesignated electrode of electrodes 26 is used to measure the resultingcurrents. Alternatively, as illustrated in FIG. 10, the electrodecontrol 14 could be fixed and apply only one discrete voltage pattern.The measurements are taken from alternately switched electrodes. Ineither case, a resulting series of currents from the sensor head 12 isobtained.

The discrete voltage patterns or electrode configuration can bespecialized to sense material at specific layer thicknesses. Forexample, the measurement obtained by one voltage pattern or electrodeconfiguration could be most sensitive to material within a 1 mmthickness while other configuration is sensitive to layer thicknesses ofup to 5 mm.

In the preferred embodiment, the voltage patterns represent Besselfunctions. Three distinct patterns as illustrated in FIG. 8 can be used.Each discreet voltage pattern vary sinusoidally with time at a fixedmagnitude and phase. For detection of substances which are likely to befound on an aircraft surface, a sinusoidal frequency of 1 MHz has beenfound to be suitable. The three patterns differ in the initial periodand the rate of decrease in period.

Each configuration creates an electric field that produces a current inthe electrodes. The magnitude and phase of this current depends on theelectrical characteristics and the thickness of the substance present onthe sensor surface. The sensitivity of each configuration to thematerial being measured decays exponentially as a function of its depth.Each measurement configuration has a different rate of decay that ischaracterized spectrally by its dominant spatial wavelength such thatthe degree of penetration is intentional and unique to each.

Referring to FIG. 6, sensor head 12 is schematically illustrated havinga plurality of concentric electrode rings 26 a-p. Each ring iselectrically connected to the electrode control 14. Ring e iselectrically connected to the amplitude and phase measurement system 16.The electrode control 14 applies a voltage pattern to each of theconcentric electrode rings. The amplitude and phase measurement system18 will measure the responsive current from a designated one of theconcentric electrodes 26, ring e.

The electrode control 14 establishes and switches between eachconfiguration of FIG. 8. Sense circuit 58 measures the three resultantcurrents imposed in the designated one of the electrodes 26, ring e.Each of the resultant currents is successively digitized to form sixdata inputs. A temperature measurement is taken from thermistor 29 andthe seven pieces of data will form a measurement set. The measurementset is transferred from the amplitude and phase measurement system 16 tothe communications system 18 to the computer 20 for processing using theinversion software.

Communications system 18 can be any suitable form of data transmission.The resultant current received from the amplitude and phase measurement16 is in an analog format. Communications system 18 can either transmitthe data in an analog format and convert to a digital format prior tofinal transmission to the computer 20. Preferably, the data is convertedimmediately into digital and transmitted in a digital format to computer20.

For use as an substance detector, the sensor head 12 is installed in awing or tail surface of an aircraft. The remaining hardware of thesystem can be installed; in the main body of the aircraft withelectrical connections extending between the sensor head and hardware.The display can be mounted in the cockpit for easy review by the pilotor other flight officer.

The sensor head should be placed on the leading 10% of the wing or tailsurface. This will allow the sensor to detect inflight icing, yet willbe sufficiently level for accurate ground ice monitoring. In mostcommercial aircraft this will permit the installation of the sensor head12 behind the bleed air heated region and in front of the fuel tank. Atthis point, the curvature of the wing is sufficiently small to allow thesensor head 12 to have a 60 mm diameter to fit inconspicuously and withno significant change in wing geometry. The sensor head 12 should bemounted flush to the wing surface to present a minimal disturbance tothe air flow.

When the preferred embodiment is used in an aircraft, governmentregulations require that the sensor head 12, the electrode control 14,the amplitude and phase measurement 16 and communications system 18 meetthe emissions requirements outlined in FCC Part 15, Subpart B Class A,15.107(a) (Conducted Emissions) and 15.109(a) (Radiated Emissions).Further, the sensor head 12 should be in conformance with MIL-STD-461C,RS03, as well as other standards as may be applicable.

In very general terms, a measurement set is generated by the sensor headand transferred to computer 20. The analytical software within computer20 then approximates the profile of the physical structure of thesubstances overlying the sensor head 12. Artificially intelligentinversion routines incorporating previously measured and theoreticalmaterial signatures are able to identify substances and their thicknessgiven the sensed currents.

Referring to FIG. 7, the analytical techniques will be described indetail.

The computer of the present invention comprises a ground computer 19 andan on-board computer 20. The ground computer 19 creates, stores andmanages a main database which is used to create a map which is used totransform a measurement set of data into a profile. Optionally, theground computer can have the capability of simulating the on-boardcomputer 20.

The ground computer 19 stores a sample database 66 containing archivedcontrolled measurements. Initial sample measurements are taken onrelatively simple Configurations. For example, the sample measurementsmay generate data for scattered droplets, uneven mixing, irregularlayering, contamination and variations due to local and environmentalfactors. These sample measurements are indexed and stored together withthe estimates of their corresponding profile.

The main database also includes theoretical database 68 which enhancesthe sample database 66 by using theoretical models to fill in the gapsbetween the measured data. The theoretical set of data is created fromtheoretical models. For example, the theoretical set may generate datafor mixtures and layers of water and de-icing fluid. The theoretical setis stored together with the estimates of their corresponding profiles.

For implementation of the system as a substance detector, the probablesubstances which can be expected to overlay the sensor head areidentified, such as air, ice, snow, slush, din, water and de-icing oranti-icing fluids. The data relevant to the probable substances is thenextracted from the main database by interpretation function 70. The datais transformed into a set of vectors which define the vector space.

The vector space is reorganized and broken down into two subsets ofsubregions with less variation than the parent set. An estimate of thepotential for further subdivision is calculated and stored as well as aboundary function of the hyperplane dividing the subregions. Thehyperplane will determine a hierarchial boundary dividing the variousregions of the vector space. If a predetermined criteria regarding theseparability of data is not satisfied, a profile function is createddescribing the distribution of profiles in that region.

If predetermined criteria regarding the separability of data issatisfied, the next region which has the highest potential forsubdividing is then selected and subdivided into two further subregions.The process of subdividing is repeated until no region of sufficientpotential for subdividing exists.

A map of the regions of the vector space is thus created by collecting aset of boundary functions describing the hierarchial boundaries and aset of profile functions describing the distribution of profiles in eachregion. In other words, the map is a partition of the vector space intoregions corresponding to known profiles, regions of unknown substancesand regions corresponding to functions for building profiles of knownsubstances. The map also includes a predetermined limit on .thevariation of the corresponding profile.

Only the map is loaded into the on-board computer 20. The memoryrequirements of the on-board computer 20 is greatly reduced incomparison to the requirements of the ground computer 19 which storesthe entire main database. This permits the on-board computer 20 to be aconventional personal computer with an INTEL 286 or equivalentprocessor. By using a map rather than a database, the speed at whichsubstances can be identified is greatly enhanced. Substances can beidentified in real-time for substantially instantaneous identificationand quantification.

In use, a raw measurement set of data from the sensor head 12 isgenerated depending upon the substances overlying the sensor head 12.The raw measurement set is corrected for temperature variations. Themeasurement set is then transformed into a test vector of predeterminedcharacteristics. The predetermined characteristics are in terms of aseven dimensional test vector defined by three complex measurements ofimpedances (or inversely admittances) and temperature. Optionally, timemay be included as an eighth dimension to analyze evolving materialssuch as degrading de-icing fluids. Further extensions to any arbitrarynumber of dimensions can be made using non-linear independentcombinations of primary basis elements.

The computer 20 must "decide" whether the test vector matches any one ofthe regions in the vector space. The interpretation routine 64 appliesthe test vector to the map by first applying the test vector to the setof boundary functions. The result identifies a small number of possibleconfigurations for the substance overlying the sensor. Theinterpretation routine 64 then specifically identifies the region inwhich the test vector falls by comparing where the test vector exists inrelation to the hierarchial boundaries. Once the interpretation routine64 identifies the region of the vector space, the local function of theset of profile functions is executed to determine the local profile.

Any electrical instrument is subject to a certain degree of electricalnoise. It is important to lessen the effect that this noise might haveon the determination of a final result.

In order to provide a stable estimate of the true profile overlying thesensor head 12, small amounts of random numerical noise is added to themeasurement set generating another test vector. The process of applyingthe test vector to the map is repeated. This step is known as dithering.Dithering is used to lessen any dependence of the measurement set whichmay exist on the inherent electronic noise. Generally, eight to sixteenpasses have been found to be satisfactory. The number of passes isrestricted to an integral power of two in order to reduce the averagingprocedure to a simple bit shift.

The profiles generated by the numerical dithering are combined to asingle profile. The variation of the profile is used to weight thesingle profile. The variation also provides an estimate of thereliability of the measurement set. If the variation is greater than thepredetermined limit, the substances overlying the sensor head 12 has notbeen identified. If less than or equal to the predetermined limit, thesubstance overlying the sensor head has been identified and quantified.The variation will also reflect the certainty of the identification.

If the substances overlying the sensor head has been identified andquantified, the measurement set is stored in a memory together with thecorresponding interpretation of the measurement set. Periodically, thestored data may be downloaded to the ground computer to be added to themain database. When data has been collected in such manner, itsinterpretation can be corrected, with respect to materials andstructure, by an "expert" user at 74. In this manner, artificiallyintelligent routines can be used to enhance the quality of the map whichcan be generated. The creation and maintenance of the map and theoperation of the invention are described in further detail. A map meansfor installation into the interpretation routine 64 is created by thefollowing steps:

(a) identifying the probable substances which are likely to be overlyingthe surface, such as air, ice, snow, slush, din, water and de-icing oranti-icing fluids,

(b) selecting data in a vector format from the database corresponding tothe probable substances defining a vector space,

(c) dividing the selected data into subsets or subregions of the vectorspace defining boundary functions describing the hierarchial boundariesbetween the subsets, defining a profile function describing thedistribution of the data in each subset;

(d) subdividing the selected data until each subset satisfiespredetermined criteria for subdividing;

(e) collecting the set of boundary and profile functions in a map.

The map can then be loaded into the interpretation routine 64. Theanalysis of a measurement set of the resulting currents is carried outin the following steps:

(a) A raw measurement set is input to the on-board computer 20 from thesensor through communications system 18. The measurement set includesthree complex impedances in magnitude and phase form, temperatureinformation, and optionally time.

(b) The raw measurement set is calibrated by temperature calibration 72,and convened to a vector format for input to the interpretation routine64.

(c) The local profile corresponding to the measurement set is determinedby applying the measurement set to the map means.

(d) The local profile is refined by numerical dithering of themeasurement set. Reliability is tested by calculating the variation ofthe refined local profile.

(e) If the variation is greater than the predetermined limit, thesubstances overlying the sensor head has not been identified. If lessthan the predetermined limit, substance overlying the sensor head hasbeen identified and quantified. Actions to be taken, such as signallingalarms, are effected.

(f) If the substances overlying the sensor head has been identified andquantified, the measurement set is stored in a memory together with thecorresponding profile of the measurement set. Periodically, the storeddata process may be downloaded to the ground computer to be added to themain database.

The operation of the invention may be described in terms of thefollowing example. The three patterns A, B and C of FIG. 8 are appliedto a sensor head. Overlying the sensor head is a sample of snow at -5°C. The current from ring e is the input to sense circuit 58. Sensecircuit 58 amplifies the current and converts the input current to avoltage. The output of the sense circuit 58 is as follows in Table 1:

                  TABLE 1                                                         ______________________________________                                                 MAGNITUDE   MAGNITUDE                                                PATTERN  V.sub.1 [mV RMS]                                                                          V.sub.0 [mV RMS]                                                                          PHASE [DEG]                                  ______________________________________                                        A        480.08      118.381     -40.88                                       B        480.20      159.604     -35.98                                       C        480.32      207.725     -30.07                                       ______________________________________                                    

These values are transferred to the vector voltage measurement circuit60. Voltage measurement circuit 60 converts the sinusoidal signal to aDC type signal. The voltage measurement circuit then scales the voltagevalues to a voltage between 0 and 10 volts. The output of circuit 60 isas follows in Table 2:

                  TABLE 2                                                         ______________________________________                                        PATTERN     MAGNITUDE (V) PHASE (V)                                           ______________________________________                                        A           2.04090       7.28814                                             B           2.75158       6.79767                                             C           3.58120       6.20749                                             ______________________________________                                    

These values are then digitized in digitization circuit 61. The outputof digitization is as follows in Table 3:

                  TABLE 3                                                         ______________________________________                                        PATTERN         MAGNITUDE   PHASE                                             ______________________________________                                        A               0.246586    -40.8814                                          B               0.332369    -35.9767                                          C               0.432472    -30.0749                                          ______________________________________                                    

The input voltage patterns A, B and C vary with respect to time in afixed magnitude and phase. Accordingly, the measurements are taken overa period of time to obtain minimum and maximum values and averagevalues. In the preferred embodiment, a time period of 30 ms is used. Thetime period should be sufficiently short to avoid fluctuation problemswith changing physical conditions on the sensor surface. A full set ofsample data from the sensor head is a set of 27 real numbers, in ASCIIformat. Table 4 is a sample reading taken of air at 24° C.

                                      TABLE 4                                     __________________________________________________________________________    PROPERTY AVERAGE    MINIMUM    MAXIMUM                                        __________________________________________________________________________    A Magnitude                                                                            2.423037 × 10.sup.-1                                                               2.418614 × 10.sup.-1                                                               2.427494 × 10.sup.-1                     A Phase  -4.135507 × 10.sup.-1                                                              -4.124039 × 10.sup.-1                                                              -4.144810 × 10.sup.-1                    A Temperature                                                                          2.428713 × 10.sup.-1                                                               2.425604 × 10.sup.-1                                                               2.430692 × 10.sup.-1                     B Temperature                                                                          3.281975 × 10.sup.-1                                                               3.277824 × 10.sup.-1                                                               3.286453 × 10.sup.-1                     B Phase  -3.652611 × 10.sup.-1                                                              -3.642485 × 10.sup.-1                                                              -3.658522 × 10.sup.-1                    B Temperature                                                                          2.427846 × 10.sup.-1                                                               2.425604 × 10.sup.-1                                                               2.429613 × 10.sup.-1                     C Magnitude                                                                            4.272364 × 10.sup.-1                                                               4.267879 × 10.sup.-1                                                               4.278819 × 10.sup.-1                     C Phase  -3.064128 × 10.sup.-1                                                              -3.057229 × 10.sup.-1                                                              -3.072710 × 10.sup. -1                   C Temperature                                                                          2.427653 × 10.sup.-1                                                               2.424371 × 10.sup.-1                                                               2.429459 × 10.sup.-1                     __________________________________________________________________________

The data is converted to machine code (ASCII format) and a simple checkis carried out to assess whether the data has been corrupted by signalnoises or other sources. The average value of the data is comparedagainst the corresponding minimum and maximum values. If the resultindicates that the data is valid, each set of magnitude and phase valuesare converted from an impedance to an admittance.

The data is next calibrated to remove any dependence of the data ontemperature and to correct for any long term drift in the electronics.The temperature coefficients T₀ and T₁ are created by operating a cleansensor in a temperature controlled environment. The sensor should beindependent of temperature. The variations in readings can then becalibrated such that the readings remain constant. The temperaturecoefficients T₀ and T₁ are stored within the sensor evaluation software.The drift calibration term A can be generated when required by assumingan air reading and a DATA VALUE of zero.

    A[n]=SAMPLE[n]-T.sub.0 [n]-T.sub.1 [n]×T

where T is the temperature in °C.

Table 5 is a table of typical calibration values.

                  TABLE 5                                                         ______________________________________                                        PATTERN  T.sub.0 [n] T.sub.1 [n]                                                                              A[n]    [n]                                   ______________________________________                                        A real   3.067681 × 10.sup.0                                                                 0.002285318                                                                              -0.003745                                                                             0                                     A complex                                                                              2.660739 × 10.sup.0                                                                 0.002160601                                                                              -0.004497                                                                             1                                     B real   2.428113 × 10.sup.0                                                                 0.001389255                                                                              -0.002961                                                                             2                                     B complex                                                                              1.767522 × 10.sup.0                                                                 0.001398589                                                                              -0.003790                                                                             3                                     C real   1.999283 × 10.sup.0                                                                  0.0009045687                                                                            -0.002560                                                                             4                                     C complex                                                                              1.160502 × 10.sup.0                                                                  0.0009285227                                                                            -0.02965                                                                              5                                     ______________________________________                                    

Applying these calibration factors to the raw data of Table 6, yieldsthe set of data:

                  TABLE 6                                                         ______________________________________                                        PATTERN  SAMPLE VALUE   DATA VALUE    [n]                                     ______________________________________                                        A real   3.066131       14            0                                       A complex                                                                              2.654228        9            1                                       B real   2.434807       17            2                                       B complex                                                                              1.767481       11            3                                       C real   2.000989        9            4                                       C complex                                                                              1.158763        6            5                                       ______________________________________                                    

The DATA VALUE is obtained from the SAMPLE VALUE by applying thecalibration and scaling factors as follows:

    DATA[n]=1024×(SAMPLE[n]-A[n]-T.sub.0 [n]-T.sub.1 [n]×T)

where T is the temperature in °C.

The temperature is increased by a factor of 10 to account for a decimalplace in the temperature reading and to keep the temperature in aninteger format. The results of the DATA VALUE is combined withtemperature and a unit element. The unit element is a constant whichwill ensure that the inner product comes out as either a positive ornegative value. The resultant test vector is as follows:

    V=[14,9,17,11,9,6,-50,1]

The next step in the process is the mapping of the test vector to aregion of the vector space. This is carried out by building up a numberof profiles using the dithered values in the test vector and thencombining them to present a final profile.

A major profile M is a two dimensional matrix whose numbers of rowsequal that of the number of possible materials to be tested and whichhas 128 columns, each of which corresponds to a material layer one tenthof a millimeter thick. The major profile M is initialized to contain allzeros.

A minor profile m is initialized in the same manner, except that a"guess" is made as to the material overlying the sensor head. This canbe represented in Table 7, assuming the first guess is air and the firsteight tenths of a millimeter.

                  TABLE 7                                                         ______________________________________                                        un-   0      0      0    0    0    0    0    0    . . .                       known                                                                         air   15     15     15   15   15   15   15   15   . . .                       snow  0      0      0    0    0    0    0    0    . . .                       ice   0      0      0    0    0    0    0    0    . . .                       water 0      0      0    0    0    0    0    0    . . .                       . . . . . .  . . .  . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                            de-   0      0      0    0    0    0    0    0    . . .                       icing                                                                         fluid                                                                         ______________________________________                                    

The numerical values in the table indicate a measure of certainty, with0 being the least and 15 being the highest.

The map describing the vector space consists of a series of datastructures. Each structure contains a variety of digital information.The information may include a numerical description of a boundarybetween the regions divided, an instruction for correcting the currentprofile estimate, a means to estimate the validity of the test vector,and indices to the next level of decision.

The numerical description of a boundary is in form, a test vector.Mathematically the vector describes the hyperplane separating tworegions of the vector space. The inner product of boundary B and thecurrent dithered test vector D, B·D yields an integer value whose signindicates which region for examination is to be chosen and whose signedvalue is used to determine the validity of the interpretation. Returningto the example of the snow reading, the hyperplane boundary between highpermittivity materials such as water or de-icing fluid and lowpermittivity materials such as ice, snow could be as follows:

    B=[143,78,52,63,25,30,0,-3762]

The inner product yields

    B·D=1136>0

indicating that the positive branch data structure should be the nextchosen. In other words, the inner product indicates that the assumptionthat the sensor is clean is wrong.

This choice is conditional upon the acceptance of the inner productvalue at the next level. Each branch of the tree maintains an expectedvalue for the inner product result from the previous level together withminimum and maximum expected deviations for this value. Should the innerproduct value fall outside this range, the construction procedure isterminated. By terminating the procedure, the minor profile nowrepresents an estimate of the distribution of all profiles fallingwithin the any subregions underlying the current region.

Simultaneously, the minor profile m is updated in the regions wherebetter information has been obtained. Only the updated minor profile mis stored in memory. The profile after being updated might read as inTable 8:

                  TABLE 8                                                         ______________________________________                                        un-   6      7      7    7    8    10   12   14   . . .                       known                                                                         air   0      0      0    0    0    0    0    0    . . .                       snow  4      4      4    8    7    5    3    1    . . .                       ice   4      4      4    2    1    0    0    0    . . .                       water 1      0      0    0    0    0    0    0    . . .                       . . . . . .  . . .  . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                       de-   0      0      0    0    0    0    0    0    . . .                       icing                                                                         fluid                                                                         ______________________________________                                    

This table indicates that there is some recognition that there is ice orsnow over the surface, or perhaps an extremely thin layer of water.However, this recognition is quite tentative. The table does confirmthat the existence of de-icing fluid and the hypothesis that the sensoris clean have been rejected.

The process of boundary comparison, profile correction, and datastructure selection is repeated until the relevant boundaries have beenexhausted. The final subregion in which the dithered data points fallmight force the construction as in Table 9:

                  TABLE 9                                                         ______________________________________                                        Dis-                                                                          tance 0.1    0.2    . . .                                                                              1.8  1.9  2.0  2.1  2.2  . . .                       ______________________________________                                        un-   0      0      . . .                                                                              0    0    0    0    0    . . .                       known                                                                         air   0      0      . . .                                                                              0    6    9    15   15   . . .                       snow  15     15     . . .                                                                              15   9    6    0    0    . . .                       ice   0      0      . . .                                                                              0    0    0    0    0    . . .                       water 0      0      . . .                                                                              0    0    0    0    0    . . .                       . . . . . .  . . .  . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                       de-   0      0      . . .                                                                              0    0    0    0    0    . . .                       icing                                                                         fluid                                                                         ______________________________________                                    

In this example, the table indicates that the certainty that there is upto 1.8 mm of snow on the sensor is strong. The air-snow boundary occursbetween 1.8 and 2.1 mm. The other material which could be overlying thesensor have been rejected.

The minor profile m is then added to the major profile M and the processis repeated for the next dithered test vector. The next dithered testvector will produce a second minor profile m. The minor profiles arethen averaged by summation and subsequent shifting to produce a finalmajor profile M. In this example the final major profile M might be asin Table 10:

                  TABLE 10                                                        ______________________________________                                        Dis-                                                                          tance 0.1    0.2    . . .                                                                              1.8  1.9  2.0  2.1  2.2  . . .                       ______________________________________                                        un-   0      0      . . .                                                                              0    0    0    0    0    . . .                       known                                                                         air   0      0      . . .                                                                              0    3    9    14   15   . . .                       snow  15     15     . . .                                                                              15   12   1    0    0    . . .                       ice   0      0      . . .                                                                              0    0    0    0    0    . . .                       water 0      0      . . .                                                                              0    0    0    0    0    . . .                       . . . . . .  . . .  . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                                                                              . . .                       de-   0      0      . . .                                                                              0    0    0    0    0    . . .                       icing                                                                         fluid                                                                         ______________________________________                                    

The result is then transferred to the display. The major profile M canbe graphically displayed. Brighter shades correspond to higher degreesof certainty while lower shades to lesser certainty. Alternatively, therows of the table can be integrated to display simply the existence ornon-existence of a material overlying the sensor.

In the preferred embodiment, the geometry of the sensor electrodes is aplurality of concentric circular electrodes. FIG. 9 illustrates otherpossible electrode configurations which may be used.

An electrode arrangement must be designed such that it can be referencedby a standard co-ordinate system. For example, a set of parallel stripelectrodes could be represented in rectangular coordinates. In thiscase, the discrete voltage pattern applied to the electrodes is a sinewave and the resulting pattern could be numerically represented by aFourier series.

This option has inherent disadvantages over the concentric circularelectrode system. A rectangular pattern of parallel electrodes wouldhave to be represented in two dimensions unless the electrodes could beconsidered to be infinitely long. This would require additionalcomplexity during the sensor design.

The preferred embodiment has been described in terms of a device andmethod for identifying and quantifying substances on an aircraftsurface. However, it is apparent that the preferred embodiment could beused to identify and quantify any substance on any surface. Forinstance, such devices could be used to identify the relative make-up aflow of fluid through a pipe by installing a series of sensors about thepipe's inside surface.

It is to be understood that the scope of the present invention is not tobe limited to the specific embodiments described above. The inventionmay be practised other than as particularly described and still bewithin the scope of the accompanying claims.

We claim:
 1. An apparatus for identifying and quantifying in real timesubstances overlying a surface, the apparatus comprising:a plurality ofelectrodes underlying a surface, an electrode control means, connectedto the plurality of electrodes, for applying a voltage pattern to theelectrodes to define an electric field at the surface of a type whichinduces a plurality of currents in the electrodes which currents varyaccording to a substance overlying the the surface, an amplitude andphase measurement means connected to the plurality of electrodes and tothe electrode control means for sensing a plurality of currentsresponsive to the electric field and converting the sensed currents to ameasurement set, and computer means having a memory for storing a mapmeans of probable substances which could be overlying the surface, saidmap means being a partition of a vector space of predeterminedcharacteristics of said probable substances into regions of profilescorresponding to an identity and quantity of said substances, saidcomputer means having a processor for correlating the measurement setwith the partition of vector space in the map means thereby identifyingand quantifying the substances overlying the surface and for generatingan output signal corresponding to the identity and quantity ofsubstances overlying the surface, and display means responsive to theoutput signal for displaying the identity and quantity of substancesoverlying the surface.
 2. An apparatus as claimed in claim 1 whereinsaid apparatus further includes electronic storage means for storing adatabase from which said map means is generated, said databasecomprising sample data of sample measurements of the probable substancesand quantities thereof together with estimates of corresponding profilesof the sample data and theoretical data of the probable substances andquantities thereof together with corresponding profiles of thetheoretical data.
 3. An apparatus as claimed in claim 2 wherein said mapmeans is generated by(a) selecting the probable substances which arelikely to be overlying the surface, (b) selecting data from the databasecorresponding to the probable substances, (c) successively dividing theselected data into subsets and defining a boundary function describinghierarchial boundaries between the subsets, the subsets being divideduntil each subset satisfies a predetermined criteria for subdividing,(d) defining a profile function describing the distribution of the datain each subset; and (e) collecting a set of boundary and profilefunctions.
 4. An apparatus as claimed in claim 3 wherein said computermeans correlates the measurement set with the generated map means by(a)defining a local profile by applying the measurement set to the mapmeans, (b) refining the local distribution by numerical dithering of themeasurement set, (c) calculating the variation of the refined localdistribution, (d) comparing the variation with a predetermined limit andif the variation is greater than a predetermined limit, sending theoutput signal that the substance has not been identified and if thevariation is less than or equal to the predetermined limit sending theoutput signal corresponding to the identity and quantity of thesubstances detected.
 5. An apparatus as claimed in claim 4 wherein saidmeasurement set and corresponding profile of substances overlying thesurface is stored in the electronic memory means for addition to thedatabase.
 6. An apparatus as claimed in claim 5 wherein said measurementset is a vector having a plurality of dimensional regions, eachcorresponding to the predetermined characteristics.
 7. An apparatus asclaimed in claim 6 wherein said predetermined characteristics are threecomplex measurements of impedance and temperature.
 8. An apparatus asclaimed in claim 7 wherein said predetermined characteristics furtherincludes time.
 9. An apparatus as claimed in claim 4 wherein saidplurality of electrodes is imbedded in a sensor head and said surface isdefined by the top surface of said sensor head.
 10. An apparatus asclaimed in claim 9 wherein said sensor head comprises a protectivelayer, an electrode layer, a backing layer and a ground plane layer,said protective layer is said top surface, said electrode layer has saidplurality of electrodes imbedded therein and said layers are integrallymoulded together and having connector pins extending from said pluralityof electrodes through the backing layer and insulated from the groundplane layer and having one connector pin extend through metallized boresin the backing layer and hermetically joined to said ground plane layergrounding the electrode.
 11. An apparatus as claimed in claim 9 whereinsaid sensor head further comprises a temperature sensing means imbeddedtherein.
 12. An apparatus as claimed in claim 11 wherein said sensorhead further comprises a thermistor imbedded in the backing layer andhaving connector pins electrically connecting the thermistor andextending through the backing layer.
 13. An apparatus as claimed inclaim 12 wherein said plurality of electrodes is a series of concentricrings and said electric field approximates a Bessel function whichvaries sinusoidally with respect to time and having a fixed magnitudeand phase.
 14. An apparatus as claimed in claim 13 wherein saidelectrode control means applies a discreet voltage to each of theconcentric ring to define said electric field spatially and saidcurrents are sensed from a preselected ring of the plurality ofelectrodes.
 15. An apparatus as claimed in claim 14 wherein saidelectrode control means applies a voltage pattern to a preselected ringof the electrodes to define the electric field spatially and thecurrents are sensed successively from each of the rings of the pluralityof electrodes.
 16. An apparatus for identifying and measuring substancesoverlying a surface, the apparatus comprising:a sensor head comprising aprotective layer having a top surface, an electrode layer having aplurality of concentric electrodes imbedded therein, a backing layerhaving temperature means for generating a signal dependent ontemperature and a ground plane layer, connector pins extending from saidplurality of electrodes and said temperature means through the backinglayer and insulated from the ground plane layer, a grounding pin forgrounding one electrode to the ground plane layer, said layersintegrally moulded together, an electrode control means connected to theplurality of electrodes for defining an electric field at the topsurface, said electric field approximating a Bessel function whichvaries sinusoidally with respect to time and which has a fixed magnitudeand phase, an amplitude and phase measurement means connected to theplurality of electrodes and to the electrode control means for measuringthe a plurality of currents responsive to the electric field andconverting the currents to a measurement set comprising at least sevendimensional regions defined by three complex measurements of impedanceand temperature, and a first computer means having a memory for storinga map means comprising a partition of a vector space of predeterminedcharacteristics of substances into regions of profiles corresponding tothe substances which could be overlying the surface, said computer meanshaving a processor for correlating the measurement set with the mapmeans thereby identifying and quantifying the substances overlying thesurface and for generating an output signal corresponding to theidentity and quantity of substances overlying the surface, and displaymeans responsive to the output signal for displaying the identity andquantity of substances overlying the surface.
 17. An apparatus asclaimed in claim 16 wherein said apparatus further includes a secondcomputer means for storing a database comprising sample data of samplemeasurements of the probable substances and quantities thereof togetherwith estimates of corresponding profiles of the sample data andtheoretical data of the probable substances and quantities thereoftogether with corresponding profiles of the theoretical data, the secondcomputer means remote from said first computer means, said map means isgenerated by(a) selecting the probable substances which are likely to beoverlying the surface, (b) selecting data from the databasecorresponding to the probable substances, (c) successively dividing theselected data into subsets defining hierarchial boundaries between thesubsets, the subsets being divided until each subset satisfies apredetermined criteria for subdividing, (d) defining a functiondescribing the distribution of the data in each subset.
 18. An apparatusas claimed in claim 17 wherein said computer means correlates themeasurement set with the map means by(a) defining a local profile byapplying the measurement set to the map means, (b) refining the localdistribution by numerical dithering of the. measurement set, (c)calculating the variation of the refined local distribution, (d)comparing the variation with a predetermined limit and if the variationis greater than a predetermined limit, sending the output signal thatthe substance has not been identified and if the variation is less thanor equal to the predetermined limit sending the output signalcorresponding to the identity and quantity of the substances detected.19. An apparatus as claimed in claim 18 wherein said apparatus,excluding the second computer means, is installed on an aircraft and thesensor head is installed flush with a wing or tail surface on theleading 10% thereof.
 20. An apparatus as claimed in claim 19 wherein theprobable substances includes air, ice, snow, slush, dirt, water andde-icing or anti-icing fluids.
 21. An apparatus as claimed in claim 20wherein a measurement set and corresponding profile of a substance bythe apparatus is stored and periodically downloaded to the secondcomputer means for enhancing the database.
 22. An apparatus as claimedin claim 21 wherein said electrode control means applies a discreetvoltage to each of the concentric rings to define said electric fieldspatially and said currents are sensed in a preselected ring of theelectrodes.
 23. An apparatus as claimed in claim 21 wherein saidelectrode control means applies a voltage pattern to the electrodes todefine the electric field spatially and the currents are sensedsuccessively from the rings of electrodes.
 24. A method for identifyingand measuring substances overlying a surface using a plurality ofconcentric electrodes underlying a surface, an electrode control meansconnected to the plurality of electrodes for defining an electric fieldat the surface, an amplitude and phase measurement means connected tothe plurality of electrodes and to the electrode control means formeasuring a plurality of currents responsive to the electric field,computer means having a memory for storing a map means comprising apartition of a vector space of predetermined characteristics ofsubstances into regions of profiles, and a display means responsive toan output signal for displaying the identify and quantity of substancesoverlying the surface, the method comprising the steps of:(a) applyingan electric field at the surface, (b) measuring a plurality of currentsresponsive to the electric field, (c) converting the currents to ameasurement set, and (d) correlating the measurement set with the mapmeans thereby identifying and quantifying the substances overlying thesurface, and (e) generating an output signal corresponding to theidentity and quantity of substances overlying the surface.
 25. A methodas claimed in claim 24 wherein said map means is generated by(a)selecting the probable substances which are likely to be overlying thesurface, (b) selecting data from a database corresponding to theprobable substances, said database comprises sample data of samplemeasurements of the probable substances and quantities thereof togetherwith estimates of corresponding profiles of the sample data andtheoretical data of the probable substances and quantities thereoftogether with corresponding profiles of the theoretical data, (c)successively dividing the selected data into subsets defininghierarchial boundaries between the subsets, the subsets being divideduntil each subset satisfies a predetermined criteria for subdividing,(d) defining a function describing the distribution of the data in eachsubset.
 26. A method as claimed in claim 25 wherein said computer meanscorrelates the measurement set with the map means by(a) defining a localprofile by applying the measurement set to the map means, (b) refiningthe local distribution by numerical dithering of the measurement set,(c) calculating the variation of the refined local distribution, (d)comparing the variation with a predetermined limit and if the variationis greater than a predetermined limit, sending the output signal thatthe substance has not been identified and if the variation is less thanor equal to the predetermined limit sending the output signalcorresponding to the identity and quantity of the substances detected.27. A method as claimed in claim 26 wherein a measurement set andcorresponding profile of a substance by the apparatus is stored andperiodically downloaded to the second computer means for enhancing thedatabase.
 28. A method as claimed in claim 27 wherein said electrodecontrol means successively applies a plurality of discreet voltagepatterns to each of the concentric electrodes to define said electricfield spatially and said currents are sensed from a preselected one ofthe electrodes.
 29. A method as claimed in claim 28 wherein said voltagepattern varies sinusoidally with respect to time at a fixed magnitudeand phase.
 30. A method as claimed in claim 27 wherein said electrodecontrol means applies a voltage pattern to the electrodes to define theelectric field spatially and the currents are sensed successively fromthe electrodes.
 31. A method as claimed in claim 31 wherein said voltagepattern varies sinusoidally with respect to time at a fixed magnitudeand phase.